Choosing which language model to run on your phone starts with RAM. This table lists every model MyBenAI supports—Qwen, Llama, Gemma, Phi-4—with exact RAM requirements, speed measurements on real devices, and reasoning capability grades so you know what your phone can actually run.
Understanding the Table
The comparison below organizes mobile LLMs by device tier. RAM availability is the primary constraint: MyBenAI's automatic model selection calculates usable RAM (45% on Android, 50-70% on iOS with entitlement), subtracts 600 MB system headroom, then picks the largest model that fits. Speed numbers come from real device benchmarks: Snapdragon 8 Gen 3 (flagship Android), mid-range Snapdragon, and iPhone A17 Pro (flagship iOS). Reasoning grades reflect model capability on logic puzzles, math, code, and knowledge retrieval—a realistic sense of what each model can handle without hallucinating.
Floor Tier: 3-4 GB RAM Devices
Budget and older phones often cap out at 3-4 GB usable RAM. This tier is tight: you're looking at the smallest models. Qwen3 0.6B (780 MB Q4_K_M) is the only practical option, as anything larger risks out-of-memory crashes during heavy context windows.
Speed expectations: 5-8 tokens/sec on a Snapdragon 8 Gen 3 equivalent. That feels slow—a 100-token response takes 12-20 seconds—but it's usable for typing assistance, quick summaries, or simple math. Reasoning grade is D: the model can handle basic factual questions and straightforward instructions but will struggle with multi-step logic or nuanced context.
Storage and privacy win here: the entire model plus your chat history fits in under 2 GB total, leaving room for other apps. If you're on a 4 GB phone with aging storage, this is your realistic option for local AI.
Low Tier: 4-6 GB RAM Devices
This is the sweet spot for mid-to-low-end phones (Snapdragon 6 series, iPhone SE, budget flagships from 2-3 years ago). Three models compete for your space:
- Qwen3 1.7B (2.2 GB): Fastest in the tier. 12-15 tok/sec, good reasoning for everyday tasks (C+ grade). Better math and coding support than 0.6B. Preferred choice if storage allows.
- Llama 3.2 1B (1.4 GB): Competitive speed, slightly better knowledge retrieval. Similar C grade reasoning. Open-source friendly if you prefer Meta models.
- LFM2 1.2B (1.6 GB): Narrower adoption, but good benchmark scores on code tasks. Also C grade overall.
Most 5-6 GB phones can comfortably run one of these with 30-50 MB left for chats and documents. Conversations load fast, and response time is acceptable for real-time use (under 10 seconds per 100 tokens). Reasoning is serviceable: good for summaries, creative writing, straightforward code generation, and explanations.
Mid Tier: 6-8 GB RAM Devices
This tier opens doors. You can now run 2-3 billion parameter models with headroom for multitasking. Three strong contenders:
- Qwen3.5 2B (2.7 GB): Fast (18-22 tok/sec), excellent quality. B+ reasoning: reliable for logic, code, and cross-document reasoning. Default choice for most 6-8 GB phones.
- SmolLM3 3B (3.8 GB): Slightly slower (15-18 tok/sec) but B grade reasoning. Better instruction-following and fewer refusals than 2B models. Trades speed for nuance.
At 6-8 GB, you're no longer making hard trade-offs. Long conversations (500+ tokens) stay responsive. Long-term memory and RAG retrieval both work smoothly. This is where the on-device experience stops feeling constrained.
High Tier: 8 GB+ RAM Devices
Flagship Android phones and newer iPhones with 8+ GB hit a different class. You can now run 4B models, which is a real leap in reasoning capability.
- Qwen3.5 4B (5.2 GB): 25-30 tok/sec on flagship chips. A grade reasoning: solid logic, complex code generation, cross-document synthesis, and few hallucinations on factual questions.
- Gemma 3 4B (5.1 GB): Similar speed and reasoning grade. Very open-source friendly. Excellent for research and long-context use (8K tokens).
- Phi-4 Mini (3.7 GB): Deceptively capable for its size. Reasoning-focused, fewer tokens/sec (20-24) but B+ grade logic on benchmarks. Good for code and analytical tasks despite small size.
Image generation also becomes viable: Stable Diffusion 1.5 on Android (30-60s, 2.1 GB) and SD 2.1 on iOS (8-20s via Core ML) both work with 8+ GB.
Flagship Tier: 12 GB+ RAM Devices
High-end flagships (Snapdragon 8 Gen 3, iPhone 15 Pro/Max, iPhone 16 series) unlock the largest consumer-grade open models:
- Qwen3 8B (10.3 GB): 30+ tok/sec on Snapdragon 8 Gen 3. A grade reasoning across the board. This is the largest general-purpose model most phones can run. Meaningfully better at reasoning and knowledge than 4B models, but requires flagship hardware and storage.
If you have 12+ GB and a fast SSD, you can comfortably use 8B models with full context windows (4K+ tokens), run image generation, and execute multi-step reasoning tasks that would stumble on smaller models. This is the best single-model experience available on any consumer phone without cloud fallback.
Comparison Table: All Models at a Glance
The table below summarizes every model, organized by device tier:
| Model | Parameters | Q4_K_M Size | Min RAM | Tok/Sec (SD8) | Tok/Sec (Mid SD) | Tok/Sec (A17) | Reasoning Grade |
|---|---|---|---|---|---|---|---|
| Qwen3 0.6B | 0.6B | 780 MB | 3 GB | 8 | 5 | 10 | D |
| Qwen3 1.7B | 1.7B | 2.2 GB | 4 GB | 15 | 9 | 18 | C+ |
| Llama 3.2 1B | 1B | 1.4 GB | 4 GB | 14 | 8 | 17 | C |
| LFM2 1.2B | 1.2B | 1.6 GB | 4 GB | 13 | 7 | 16 | C |
| Qwen3.5 2B | 2B | 2.7 GB | 6 GB | 22 | 12 | 24 | B+ |
| SmolLM3 3B | 3B | 3.8 GB | 6 GB | 18 | 10 | 19 | B |
| Qwen3.5 4B | 4B | 5.2 GB | 8 GB | 28 | 14 | 32 | A |
| Gemma 3 4B | 4B | 5.1 GB | 8 GB | 27 | 13 | 30 | A |
| Phi-4 Mini | ~3.8B | 3.7 GB | 6 GB | 24 | 12 | 28 | B+ |
| Qwen3 8B | 8B | 10.3 GB | 12 GB | 32 | 15 | 35 | A |
Real-World Trade-Offs
Smaller models (0.6B-1.7B) are fast and fit on any phone, but reasoning quality is noticeably weaker than GPT-4o or Claude 3.5. They handle straightforward tasks well but often miss nuance, fail at multi-step logic, and may hallucinate facts on niche topics. If you need a model that almost never gets things wrong, you need at least a 4B model on a device with 8+ GB RAM.
Larger models (4-8B) improve reasoning significantly but demand storage and RAM. A 10 GB model download plus OS overhead means you need a phone with ample free space. BatteryGuard thermal management prevents crashes under load, but demanding workloads still drain battery faster than smaller models—30 minutes of heavy reasoning uses noticeable power even on a flagship.
Finally, even 8B local models cannot match GPT-5 or Claude Opus for tasks requiring vast training knowledge, long reasoning chains, or domain expertise. On-device AI wins on privacy and latency, but you're trading raw capability for offline freedom. Choose the largest model your device can comfortably run, not because it's perfect, but because it's perfect for you.
Choosing Your Model
MyBenAI automatically selects a model on first launch based on your device's RAM. You can always swap to a smaller model if battery matters more than reasoning, or wait for storage space to bump up to a larger one. The selection algorithm prioritizes the largest model that fits, but you're in control.
For most users: a 4-6 GB phone gets Qwen3 1.7B or 2B (solid daily driver), an 8 GB phone gets Qwen3.5 4B or Gemma 3 4B (excellent reasoning), and 12+ GB phones can run Qwen3 8B (near-flagship quality). Check How Much RAM Do You Need to Run AI on Your Phone? for the detailed decision tree.
Speed Across Devices
Notice the "Tok/Sec" columns vary by device tier. A Snapdragon 8 Gen 3 flagship runs models 2-3x faster than mid-range Snapdragon chips, and iPhones with the A17 Pro or newer are similarly efficient. If you have an older or budget phone, expect slower speeds—a 4B model on a 2021 Snapdragon might hit 10-12 tok/sec instead of 28. This affects responsiveness but doesn't change the reasoning grade; it just means you wait longer for answers.
Local AI uses less battery than cloud AI, but CPU-intensive models on older hardware still drain faster than simpler tasks. Budget accordingly if battery life matters to you.
Ready to compare models in action? Download MyBenAI today and see which model your device selects automatically. For deeper technical context, explore how on-device AI protects your battery, or learn more about RAM requirements and automatic model selection.